llvm-capstone/polly
Hamza Sood 0a92aff721 Replace uses of std::iterator with explicit using
This patch removes all uses of `std::iterator`, which was deprecated in C++17.
While this isn't currently an issue while compiling LLVM, it's useful for those using LLVM as a library.

For some reason there're a few places that were seemingly able to use `std` functions unqualified, which no longer works after this patch. I've updated those places, but I'm not really sure why it worked in the first place.

Reviewed By: MaskRay

Differential Revision: https://reviews.llvm.org/D67586
2021-04-12 10:47:14 -07:00
..
cmake [Windows][Polly] Disable LLVMPolly module for all compilers on Windows 2020-09-15 09:12:38 +03:00
docs Bump the trunk major version to 13 2021-01-26 19:37:55 -08:00
include/polly Replace uses of std::iterator with explicit using 2021-04-12 10:47:14 -07:00
lib [Polly] Partially refactoring of IslAstInfo and IslNodeBuilder to use isl++. NFC. 2021-04-10 21:28:02 -05:00
test [Polly] Port DeadCodeElim to the NewPM. 2021-03-24 01:01:29 -05:00
tools Fix typos throughout the license files that somehow I and my reviewers 2019-01-21 09:52:34 +00:00
unittests [Polly] Regenerate isl-noexceptions.h. 2021-02-14 19:17:54 -06:00
utils Harmonize Python shebang 2020-07-16 21:53:45 +02:00
www [Branch-Rename] Fix some links 2021-02-01 16:43:21 +05:30
.arclint
.gitattributes
.gitignore
CMakeLists.txt Remove .svn from exclude list as we moved to git 2020-10-21 16:09:21 +02:00
CREDITS.txt
LICENSE.TXT Rename top-level LICENSE.txt files to LICENSE.TXT 2021-03-10 21:26:24 -08:00
README

Polly - Polyhedral optimizations for LLVM
-----------------------------------------
http://polly.llvm.org/

Polly uses a mathematical representation, the polyhedral model, to represent and
transform loops and other control flow structures. Using an abstract
representation it is possible to reason about transformations in a more general
way and to use highly optimized linear programming libraries to figure out the
optimal loop structure. These transformations can be used to do constant
propagation through arrays, remove dead loop iterations, optimize loops for
cache locality, optimize arrays, apply advanced automatic parallelization, drive
vectorization, or they can be used to do software pipelining.